提交 7e5eee5b 编写于 作者: A Andrey Kamaev 提交者: OpenCV Buildbot

Merge pull request #301 from emchristiansen:javasample2.4

......@@ -8,4 +8,5 @@
.. |Author_FernandoI| unicode:: Fernando U+0020 Iglesias U+0020 Garc U+00ED a
.. |Author_EduardF| unicode:: Eduard U+0020 Feicho
.. |Author_AlexB| unicode:: Alexandre U+0020 Benoit
.. |Author_EricCh| unicode:: Eric U+0020 Christiansen
.. |Author_AndreyP| unicode:: Andrey U+0020 Pavlenko
.. _Java_Dev_Intro:
Introduction to Java Development
********************************
Last updated: 12 February, 2013.
As of OpenCV 2.4.4, OpenCV supports desktop Java development using nearly the same interface as for
Android development. This guide will help you to create your first Java (or Scala) application using OpenCV.
We will use either `Eclipse <http://eclipse.org/>`_, `Apache Ant <http://ant.apache.org/>`_ or the
`Simple Build Tool (SBT) <http://www.scala-sbt.org/>`_ to build the application.
For further reading after this guide, look at the :ref:`Android_Dev_Intro` tutorials.
What we'll do in this guide
***************************
In this guide, we will:
* Get OpenCV with desktop Java support
* Create an ``Ant``, ``Eclipse`` or ``SBT`` project
* Write a simple OpenCV application in Java or Scala
The same process was used to create the samples in the :file:`samples/java` folder of the OpenCV repository,
so consult those files if you get lost.
Get OpenCV with desktop Java support
************************************
Starting from version 2.4.4 OpenCV includes desktop Java bindings.
The most simple way to get it is downloading the appropriate package of **version 2.4.4 or higher** from the
`OpenCV SourceForge repository <http://sourceforge.net/projects/opencvlibrary/files/>`_.
.. note:: Windows users can find the prebuilt files needed for Java development in the
:file:`opencv/build/java/` folder inside the package.
For other OSes it's required to build OpenCV from sources.
Another option to get OpenCV sources is to clone `OpenCV git repository
<https://github.com/Itseez/opencv/>`_.
In order to build OpenCV with Java bindings you need :abbr:`JDK (Java Development Kit)`
(we recommend `Oracle/Sun JDK 6 or 7 <http://www.oracle.com/technetwork/java/javase/downloads/>`_),
`Apache Ant <http://ant.apache.org/>`_ and `Python` v2.6 or higher to be installed.
Build OpenCV
############
Let's build OpenCV:
.. code-block:: bash
git clone git://github.com/Itseez/opencv.git
cd opencv
git checkout 2.4
mkdir build
cd build
Generate a Makefile or a MS Visual Studio* solution, or whatever you use for
building executables in your system:
.. code-block:: bash
cmake -DBUILD_SHARED_LIBS=OFF ..
or
.. code-block:: bat
cmake -DBUILD_SHARED_LIBS=OFF -G "Visual Studio 10" ..
.. note:: When OpenCV is built as a set of **static** libraries (``-DBUILD_SHARED_LIBS=OFF`` option)
the Java bindings dynamic library is all-sufficient,
i.e. doesn't depend on other OpenCV libs, but includes all the OpenCV code inside.
Examine the output of CMake and ensure ``java`` is one of the modules "To be built".
If not, it's likely you're missing a dependency. You should troubleshoot by looking
through the CMake output for any Java-related tools that aren't found and installing them.
.. image:: images/cmake_output.png
:alt: CMake output
:align: center
Now start the build:
.. code-block:: bash
make -j8
or
.. code-block:: bat
msbuild /m OpenCV.sln /t:Build /p:Configuration=Release /v:m
Besides all this will create a ``jar`` containing the Java interface (:file:`bin/opencv_2.4.4.jar`)
and a native dynamic library containing Java bindings and all the OpenCV stuff
(:file:`bin/Release/opencv_java244.dll` or :file:`bin/libopencv_java244.so` respectively).
We'll use these files later.
Create a simple Java sample and an Ant build file for it
********************************************************
.. note::
The described sample is provided with OpenCV library in the :file:`opencv/samples/java/ant` folder.
* Create a folder where you'll develop this sample application.
* In this folder create an XML file with the following content using any text editor:
.. code-block:: xml
:linenos:
<project name="SimpleSample" basedir="." default="rebuild-run">
<property name="src.dir" value="src"/>
<property name="lib.dir" value="${ocvJarDir}"/>
<path id="classpath">
<fileset dir="${lib.dir}" includes="**/*.jar"/>
</path>
<property name="build.dir" value="build"/>
<property name="classes.dir" value="${build.dir}/classes"/>
<property name="jar.dir" value="${build.dir}/jar"/>
<property name="main-class" value="${ant.project.name}"/>
<target name="clean">
<delete dir="${build.dir}"/>
</target>
<target name="compile">
<mkdir dir="${classes.dir}"/>
<javac srcdir="${src.dir}" destdir="${classes.dir}" classpathref="classpath"/>
</target>
<target name="jar" depends="compile">
<mkdir dir="${jar.dir}"/>
<jar destfile="${jar.dir}/${ant.project.name}.jar" basedir="${classes.dir}">
<manifest>
<attribute name="Main-Class" value="${main-class}"/>
</manifest>
</jar>
</target>
<target name="run" depends="jar">
<java fork="true" classname="${main-class}">
<sysproperty key="java.library.path" path="${ocvLibDir}"/>
<classpath>
<path refid="classpath"/>
<path location="${jar.dir}/${ant.project.name}.jar"/>
</classpath>
</java>
</target>
<target name="rebuild" depends="clean,jar"/>
<target name="rebuild-run" depends="clean,run"/>
</project>
.. note::
This XML file can be reused for building other Java applications.
It describes a common folder structure in the lines 3 - 12 and common targets
for compiling and running the application.
When reusing this XML don't forget to modify the project name in the line 1,
that is also the name of the `main` class (line 14).
The paths to OpenCV `jar` and `jni lib` are expected as parameters
(``"${ocvJarDir}"`` in line 5 and ``"${ocvLibDir}"`` in line 37), but
you can hardcode these paths for your convenience.
See `Ant documentation <http://ant.apache.org/manual/>`_ for detailed description
of its build file format.
* Create an :file:`src` folder next to the :file:`build.xml` file and a :file:`SimpleSample.java` file in it.
* Put the following Java code into the :file:`SimpleSample.java` file:
.. code-block:: java
import org.opencv.core.Mat;
import org.opencv.core.CvType;
import org.opencv.core.Scalar;
class SimpleSample {
static{ System.loadLibrary("opencv_java244"); }
public static void main(String[] args) {
Mat m = new Mat(5, 10, CvType.CV_8UC1, new Scalar(0));
System.out.println("OpenCV Mat: " + m);
Mat mr1 = m.row(1);
mr1.setTo(new Scalar(1));
Mat mc5 = m.col(5);
mc5.setTo(new Scalar(5));
System.out.println("OpenCV Mat data:\n" + m.dump());
}
}
* Run the following command in console in the folder containing :file:`build.xml`:
.. code-block:: bash
ant -DocvJarDir=path/to/dir/containing/opencv-244.jar -DocvLibDir=path/to/dir/containing/opencv_java244/native/library
For example:
.. code-block:: bat
ant -DocvJarDir=X:\opencv-2.4.4\bin -DocvLibDir=X:\opencv-2.4.4\bin\Release
The command should initiate [re]building and running the sample.
You should see on the screen something like this:
.. image:: images/ant_output.png
:alt: run app with Ant
:align: center
Create a simple Java project in Eclipse
***************************************
Now let's look at the possiblity of using OpenCV in Java when developing in Eclipse IDE.
* Create a new Eclipse workspace
* Create a new Java project via :guilabel:`File --> New --> Java Project`
.. image:: images/eclipse_new_java_prj.png
:alt: Eclipse: new Java project
:align: center
Call it say "HelloCV".
* Open :guilabel:`Java Build Path` tab on :guilabel:`Project Properties` dialog
and configure additional library (OpenCV) reference (jar and native library location):
.. image:: images/eclipse_user_lib.png
:alt: Eclipse: external JAR
:align: center
` `
.. image:: images/eclipse_user_lib2.png
:alt: Eclipse: external JAR
:align: center
` `
.. image:: images/eclipse_user_lib3.png
:alt: Eclipse: external JAR
:align: center
` `
.. image:: images/eclipse_user_lib4.png
:alt: Eclipse: external JAR
:align: center
` `
.. image:: images/eclipse_user_lib5.png
:alt: Eclipse: external JAR
:align: center
` `
.. image:: images/eclipse_user_lib6.png
:alt: Eclipse: external JAR
:align: center
` `
.. image:: images/eclipse_user_lib7.png
:alt: Eclipse: external JAR
:align: center
` `
.. image:: images/eclipse_user_lib8.png
:alt: Eclipse: external JAR
:align: center
` `
* Add a new Java class (say ``Main``) containing the application entry:
.. image:: images/eclipse_main_class.png
:alt: Eclipse: Main class
:align: center
* Put some simple OpenCV calls there, e.g.:
.. code-block:: java
import org.opencv.core.CvType;
import org.opencv.core.Mat;
public class Main {
public static void main(String[] args) {
System.loadLibrary("opencv_java244");
Mat m = Mat.eye(3, 3, CvType.CV_8UC1);
System.out.println("m = " + m.dump());
}
}
* Press :guilabel:`Run` button and find the identity matrix content in the Eclipse ``Console`` window.
.. image:: images/eclipse_run.png
:alt: Eclipse: run
:align: center
Create an SBT project and samples in Java and Scala
***************************************************
Now we'll create a simple Java application using SBT. This serves as a brief introduction to
those unfamiliar with this build tool. We're using SBT because it is particularly easy and powerful.
First, download and install `SBT <http://www.scala-sbt.org/>`_ using the instructions on its `web site <http://www.scala-sbt.org/>`_.
Next, navigate to a new directory where you'd like the application source to live (outside :file:`opencv` dir).
Let's call it "JavaSample" and create a directory for it:
.. code-block:: bash
cd <somewhere outside opencv>
mkdir JavaSample
Now we will create the necessary folders and an SBT project:
.. code-block:: bash
cd JavaSample
mkdir -p src/main/java # This is where SBT expects to find Java sources
mkdir project # This is where the build definitions live
Now open :file:`project/build.scala` in your favorite editor and paste the following.
It defines your project:
.. code-block:: scala
import sbt._
import Keys._
object JavaSampleBuild extends Build {
def scalaSettings = Seq(
scalaVersion := "2.10.0",
scalacOptions ++= Seq(
"-optimize",
"-unchecked",
"-deprecation"
)
)
def buildSettings =
Project.defaultSettings ++
scalaSettings
lazy val root = {
val settings = buildSettings ++ Seq(name := "JavaSample")
Project(id = "JavaSample", base = file("."), settings = settings)
}
}
Now edit :file:`project/plugins.sbt` and paste the following.
This will enable auto-generation of an Eclipse project:
.. code-block:: scala
addSbtPlugin("com.typesafe.sbteclipse" % "sbteclipse-plugin" % "2.1.0")
Now run ``sbt`` from the :file:`JavaSample` root and from within SBT run ``eclipse`` to generate an eclipse project:
.. code-block:: bash
sbt # Starts the sbt console
> eclipse # Running "eclipse" from within the sbt console
You should see something like this:
.. image:: images/sbt_eclipse.png
:alt: SBT output
:align: center
You can now import the SBT project to Eclipse using :guilabel:`Import ... -> Existing projects into workspace`.
Whether you actually do this is optional for the guide;
we'll be using SBT to build the project, so if you choose to use Eclipse it will just serve as a text editor.
To test that everything is working, create a simple "Hello OpenCV" application.
Do this by creating a file :file:`src/main/java/HelloOpenCV.java` with the following contents:
.. code-block:: java
public class HelloOpenCV {
public static void main(String[] args) {
System.out.println("Hello, OpenCV");
}
}
Now execute ``run`` from the sbt console, or more concisely, run ``sbt run`` from the command line:
.. code-block:: bash
sbt run
You should see something like this:
.. image:: images/sbt_run.png
:alt: SBT run
:align: center
Copy the OpenCV jar and write a simple application
********************************************************
Now we'll create a simple face detection application using OpenCV.
First, create a :file:`lib/` folder and copy the OpenCV jar into it.
By default, SBT adds jars in the lib folder to the Java library search path.
You can optionally rerun ``sbt eclipse`` to update your Eclipse project.
.. code-block:: bash
mkdir lib
cp <opencv_dir>/build/bin/opencv_<version>.jar lib/
sbt eclipse
Next, create the directory src/main/resources and download this Lena image into it:
.. image:: images/lena.png
:alt: Lena
:align: center
Make sure it's called :file:`"lena.png"`.
Items in the resources directory are available to the Java application at runtime.
Next, copy :file:`lbpcascade_frontalface.xml` from :file:`opencv/data/` into the :file:`resources`
directory:
.. code-block:: bash
cp <opencv_dir>/data/lbpcascades/lbpcascade_frontalface.xml src/main/resources/
Now modify src/main/java/HelloOpenCV.java so it contains the following Java code:
.. code-block:: java
import org.opencv.core.Core;
import org.opencv.core.Mat;
import org.opencv.core.MatOfRect;
import org.opencv.core.Point;
import org.opencv.core.Rect;
import org.opencv.core.Scalar;
import org.opencv.highgui.Highgui;
import org.opencv.objdetect.CascadeClassifier;
//
// Detects faces in an image, draws boxes around them, and writes the results
// to "faceDetection.png".
//
class DetectFaceDemo {
public void run() {
System.out.println("\nRunning DetectFaceDemo");
// Create a face detector from the cascade file in the resources
// directory.
CascadeClassifier faceDetector = new CascadeClassifier(getClass().getResource("/lbpcascade_frontalface.xml").getPath());
Mat image = Highgui.imread(getClass().getResource("/lena.png").getPath());
// Detect faces in the image.
// MatOfRect is a special container class for Rect.
MatOfRect faceDetections = new MatOfRect();
faceDetector.detectMultiScale(image, faceDetections);
System.out.println(String.format("Detected %s faces", faceDetections.toArray().length));
// Draw a bounding box around each face.
for (Rect rect : faceDetections.toArray()) {
Core.rectangle(image, new Point(rect.x, rect.y), new Point(rect.x + rect.width, rect.y + rect.height), new Scalar(0, 255, 0));
}
// Save the visualized detection.
String filename = "faceDetection.png";
System.out.println(String.format("Writing %s", filename));
Highgui.imwrite(filename, image);
}
}
public class HelloOpenCV {
public static void main(String[] args) {
System.out.println("Hello, OpenCV");
// Load the native library.
System.loadLibrary("opencv_java244");
new DetectFaceDemo().run();
}
}
Note the call to ``System.loadLibrary("opencv_java244")``.
This command must be executed exactly once per Java process prior to using any native OpenCV methods.
If you don't call it, you will get ``UnsatisfiedLink errors``.
You will also get errors if you try to load OpenCV when it has already been loaded.
Now run the face detection app using ``sbt run``:
.. code-block:: bash
sbt run
You should see something like this:
.. image:: images/sbt_run_face.png
:alt: SBT run
:align: center
It should also write the following image to :file:`faceDetection.png`:
.. image:: images/faceDetection.png
:alt: Detected face
:align: center
You're done!
Now you have a sample Java application working with OpenCV, so you can start the work on your own.
We wish you good luck and many years of joyful life!
......@@ -101,6 +101,26 @@ Here you can read tutorials about how to set up your computer to work with the O
:height: 90pt
:width: 90pt
* **Desktop Java**
.. tabularcolumns:: m{100pt} m{300pt}
.. cssclass:: toctableopencv
================ =================================================
|JavaLogo| **Title:** :ref:`Java_Dev_Intro`
*Compatibility:* > OpenCV 2.4.4
*Authors:* |Author_EricCh| and |Author_AndreyP|
Explains how to build and run a simple desktop Java application using Eclipse, Ant or the Simple Build Tool (SBT).
================ =================================================
.. |JavaLogo| image:: images/Java_logo.png
:height: 90pt
:width: 90pt
* **Android**
.. tabularcolumns:: m{100pt} m{300pt}
......@@ -238,10 +258,11 @@ Here you can read tutorials about how to set up your computer to work with the O
../linux_eclipse/linux_eclipse
../windows_install/windows_install
../windows_visual_studio_Opencv/windows_visual_studio_Opencv
../desktop_java/java_dev_intro
../android_binary_package/android_dev_intro
../android_binary_package/O4A_SDK
../android_binary_package/dev_with_OCV_on_Android
../ios_install/ios_install
../display_image/display_image
../load_save_image/load_save_image
../how_to_write_a_tutorial/how_to_write_a_tutorial
\ No newline at end of file
../how_to_write_a_tutorial/how_to_write_a_tutorial
<project name="SimpleSample" basedir="." default="rebuild-run">
<property name="src.dir" value="src"/>
<property name="lib.dir" value="${ocvJarDir}"/>
<path id="classpath">
<fileset dir="${lib.dir}" includes="**/*.jar"/>
</path>
<property name="build.dir" value="build"/>
<property name="classes.dir" value="${build.dir}/classes"/>
<property name="jar.dir" value="${build.dir}/jar"/>
<property name="main-class" value="${ant.project.name}"/>
<target name="clean">
<delete dir="${build.dir}"/>
</target>
<target name="compile">
<mkdir dir="${classes.dir}"/>
<javac srcdir="${src.dir}" destdir="${classes.dir}" classpathref="classpath"/>
</target>
<target name="jar" depends="compile">
<mkdir dir="${jar.dir}"/>
<jar destfile="${jar.dir}/${ant.project.name}.jar" basedir="${classes.dir}">
<manifest>
<attribute name="Main-Class" value="${main-class}"/>
</manifest>
</jar>
</target>
<target name="run" depends="jar">
<java fork="true" classname="${main-class}">
<sysproperty key="java.library.path" path="${ocvLibDir}"/>
<classpath>
<path refid="classpath"/>
<path location="${jar.dir}/${ant.project.name}.jar"/>
</classpath>
</java>
</target>
<target name="rebuild" depends="clean,jar"/>
<target name="rebuild-run" depends="clean,run"/>
</project>
\ No newline at end of file
import org.opencv.core.Mat;
import org.opencv.core.CvType;
import org.opencv.core.Scalar;
class SimpleSample {
static{ System.loadLibrary("opencv_java244"); }
public static void main(String[] args) {
Mat m = new Mat(5, 10, CvType.CV_8UC1, new Scalar(0));
System.out.println("OpenCV Mat: " + m);
Mat mr1 = m.row(1);
mr1.setTo(new Scalar(1));
Mat mc5 = m.col(5);
mc5.setTo(new Scalar(5));
System.out.println("OpenCV Mat data:\n" + m.dump());
}
}
<?xml version="1.0" encoding="UTF-8"?>
<classpath>
<classpathentry kind="src" path="src"/>
<classpathentry kind="con" path="org.eclipse.jdt.launching.JRE_CONTAINER/org.eclipse.jdt.internal.debug.ui.launcher.StandardVMType/JavaSE-1.7"/>
<classpathentry kind="con" path="org.eclipse.jdt.USER_LIBRARY/opencv-2.4.4"/>
<classpathentry kind="output" path="bin"/>
</classpath>
<?xml version="1.0" encoding="UTF-8"?>
<projectDescription>
<name>HelloCV</name>
<comment></comment>
<projects>
</projects>
<buildSpec>
<buildCommand>
<name>org.eclipse.jdt.core.javabuilder</name>
<arguments>
</arguments>
</buildCommand>
</buildSpec>
<natures>
<nature>org.eclipse.jdt.core.javanature</nature>
</natures>
</projectDescription>
eclipse.preferences.version=1
org.eclipse.jdt.core.compiler.codegen.inlineJsrBytecode=enabled
org.eclipse.jdt.core.compiler.codegen.targetPlatform=1.7
org.eclipse.jdt.core.compiler.codegen.unusedLocal=preserve
org.eclipse.jdt.core.compiler.compliance=1.7
org.eclipse.jdt.core.compiler.debug.lineNumber=generate
org.eclipse.jdt.core.compiler.debug.localVariable=generate
org.eclipse.jdt.core.compiler.debug.sourceFile=generate
org.eclipse.jdt.core.compiler.problem.assertIdentifier=error
org.eclipse.jdt.core.compiler.problem.enumIdentifier=error
org.eclipse.jdt.core.compiler.source=1.7
import org.opencv.core.CvType;
import org.opencv.core.Mat;
public class Main {
public static void main(String[] args) {
System.loadLibrary("opencv_java244");
Mat m = Mat.eye(3, 3, CvType.CV_8UC1);
System.out.println("m = " + m.dump());
}
}
A demo of the Java wrapper for OpenCV with two examples:
1) feature detection and matching and
2) face detection.
The examples are coded in Scala and Java.
Anyone familiar with Java should be able to read the Scala examples.
Please feel free to contribute code examples in Scala or Java, or any JVM language.
To run the examples:
1) Install OpenCV and copy the OpenCV jar to lib/.
This jar must match the native libraries installed in your system.
If this isn't the case, you may get a java.lang.UnsatisfiedLinkError at runtime.
2) Go to the root directory and type "sbt/sbt run".
This should generate images in your current directory.
import sbt._
import Keys._
object OpenCVJavaDemoBuild extends Build {
def scalaSettings = Seq(
scalaVersion := "2.10.0",
scalacOptions ++= Seq(
"-optimize",
"-unchecked",
"-deprecation"
)
)
def buildSettings =
Project.defaultSettings ++
scalaSettings
lazy val root = {
val settings = buildSettings ++ Seq(name := "OpenCVJavaDemo")
Project(id = "OpenCVJavaDemo", base = file("."), settings = settings)
}
}
addSbtPlugin("com.typesafe.sbteclipse" % "sbteclipse-plugin" % "2.1.0")
java -Xms512M -Xmx1536M -Xss1M -XX:+CMSClassUnloadingEnabled -XX:MaxPermSize=384M -jar `dirname $0`/sbt-launch.jar "$@"
\ No newline at end of file
此差异由.gitattributes 抑制。
import org.opencv.core.Core;
import org.opencv.core.Mat;
import org.opencv.core.MatOfRect;
import org.opencv.core.Point;
import org.opencv.core.Rect;
import org.opencv.core.Scalar;
import org.opencv.highgui.Highgui;
import org.opencv.objdetect.CascadeClassifier;
/*
* Detects faces in an image, draws boxes around them, and writes the results
* to "faceDetection.png".
*/
public class DetectFaceDemo {
public void run() {
System.out.println("\nRunning DetectFaceDemo");
// Create a face detector from the cascade file in the resources
// directory.
CascadeClassifier faceDetector = new CascadeClassifier(getClass()
.getResource("/lbpcascade_frontalface.xml").getPath());
Mat image = Highgui.imread(getClass().getResource(
"/AverageMaleFace.jpg").getPath());
// Detect faces in the image.
// MatOfRect is a special container class for Rect.
MatOfRect faceDetections = new MatOfRect();
faceDetector.detectMultiScale(image, faceDetections);
System.out.println(String.format("Detected %s faces",
faceDetections.toArray().length));
// Draw a bounding box around each face.
for (Rect rect : faceDetections.toArray()) {
Core.rectangle(image, new Point(rect.x, rect.y), new Point(rect.x
+ rect.width, rect.y + rect.height), new Scalar(0, 255, 0));
}
// Save the visualized detection.
String filename = "faceDetection.png";
System.out.println(String.format("Writing %s", filename));
Highgui.imwrite(filename, image);
}
}
\ No newline at end of file
此差异由.gitattributes 抑制。
此差异由.gitattributes 抑制。
/*
* The main runner for the Java demos.
* Demos whose name begins with "Scala" are written in the Scala language,
* demonstrating the generic nature of the interface.
* The other demos are in Java.
* Currently, all demos are run, sequentially.
*
* You're invited to submit your own examples, in any JVM language of
* your choosing so long as you can get them to build.
*/
object Main extends App {
// We must load the native library before using any OpenCV functions.
// You must load this library _exactly once_ per Java invocation.
// If you load it more than once, you will get a java.lang.UnsatisfiedLinkError.
System.loadLibrary("opencv_java")
ScalaCorrespondenceMatchingDemo.run()
ScalaDetectFaceDemo.run()
new DetectFaceDemo().run()
}
import org.opencv.highgui.Highgui
import org.opencv.features2d.DescriptorExtractor
import org.opencv.features2d.Features2d
import org.opencv.core.MatOfKeyPoint
import org.opencv.core.Mat
import org.opencv.features2d.FeatureDetector
import org.opencv.features2d.DescriptorMatcher
import org.opencv.core.MatOfDMatch
import reflect._
/*
* Finds corresponding points between a pair of images using local descriptors.
* The correspondences are visualized in the image "scalaCorrespondences.png",
* which is written to disk.
*/
object ScalaCorrespondenceMatchingDemo {
def run() {
println(s"\nRunning ${classTag[this.type].toString.replace("$", "")}")
// Detects keypoints and extracts descriptors in a given image of type Mat.
def detectAndExtract(mat: Mat) = {
// A special container class for KeyPoint.
val keyPoints = new MatOfKeyPoint
// We're using the SURF detector.
val detector = FeatureDetector.create(FeatureDetector.SURF)
detector.detect(mat, keyPoints)
println(s"There were ${keyPoints.toArray.size} KeyPoints detected")
// Let's just use the best KeyPoints.
val sorted = keyPoints.toArray.sortBy(_.response).reverse.take(50)
// There isn't a constructor that takes Array[KeyPoint], so we unpack
// the array and use the constructor that can take any number of
// arguments.
val bestKeyPoints: MatOfKeyPoint = new MatOfKeyPoint(sorted: _*)
// We're using the SURF descriptor.
val extractor = DescriptorExtractor.create(DescriptorExtractor.SURF)
val descriptors = new Mat
extractor.compute(mat, bestKeyPoints, descriptors)
println(s"${descriptors.rows} descriptors were extracted, each with dimension ${descriptors.cols}")
(bestKeyPoints, descriptors)
}
// Load the images from the |resources| directory.
val leftImage = Highgui.imread(getClass.getResource("/img1.png").getPath)
val rightImage = Highgui.imread(getClass.getResource("/img2.png").getPath)
// Detect KeyPoints and extract descriptors.
val (leftKeyPoints, leftDescriptors) = detectAndExtract(leftImage)
val (rightKeyPoints, rightDescriptors) = detectAndExtract(rightImage)
// Match the descriptors.
val matcher = DescriptorMatcher.create(DescriptorMatcher.BRUTEFORCE)
// A special container class for DMatch.
val dmatches = new MatOfDMatch
// The backticks are because "match" is a keyword in Scala.
matcher.`match`(leftDescriptors, rightDescriptors, dmatches)
// Visualize the matches and save the visualization.
val correspondenceImage = new Mat
Features2d.drawMatches(leftImage, leftKeyPoints, rightImage, rightKeyPoints, dmatches, correspondenceImage)
val filename = "scalaCorrespondences.png"
println(s"Writing ${filename}")
assert(Highgui.imwrite(filename, correspondenceImage))
}
}
\ No newline at end of file
import org.opencv.core.Core
import org.opencv.core.MatOfRect
import org.opencv.core.Point
import org.opencv.core.Scalar
import org.opencv.highgui.Highgui
import org.opencv.objdetect.CascadeClassifier
import reflect._
/*
* Detects faces in an image, draws boxes around them, and writes the results
* to "scalaFaceDetection.png".
*/
object ScalaDetectFaceDemo {
def run() {
println(s"\nRunning ${classTag[this.type].toString.replace("$", "")}")
// Create a face detector from the cascade file in the resources directory.
val faceDetector = new CascadeClassifier(getClass.getResource("/lbpcascade_frontalface.xml").getPath)
val image = Highgui.imread(getClass.getResource("/AverageMaleFace.jpg").getPath)
// Detect faces in the image.
// MatOfRect is a special container class for Rect.
val faceDetections = new MatOfRect
faceDetector.detectMultiScale(image, faceDetections)
println(s"Detected ${faceDetections.toArray.size} faces")
// Draw a bounding box around each face.
for (rect <- faceDetections.toArray) {
Core.rectangle(
image,
new Point(rect.x, rect.y),
new Point(rect.x + rect.width,
rect.y + rect.height),
new Scalar(0, 255, 0))
}
// Save the visualized detection.
val filename = "scalaFaceDetection.png"
println(s"Writing ${filename}")
assert(Highgui.imwrite(filename, image))
}
}
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